| Photovoltaic poverty alleviation project(PPAP)refers to the government-investing project that the government uniformly allocates funds to build village-level photovoltaic power plants in poverty-stricken areas with nice solar energy,and uses generation profits to help the poor.It not only solves the problems of energy supply,employment and economic construction in backward areas,but also helps to shorten the gap,maintain social equity and promote socialist modernization.The government has increased its installed capacity to 10.11 million kilowatts and benefited over 1 million households in 2 years.Due to huge positive effect,it becomes remarkable "Chinese Experience" in the exploration of poverty alleviation with Chinese characteristics and one of the focus in the 13th five-year Plan.However,with development of photovoltaic power,potential installation areas become scarce and energy abandonment is increasingly prominent.Meanwhile,with the in-depth promotion of poverty alleviation,since most projects show scattered distribution,special topography and geological variability,some adverse phenomena caused by insufficient exploration,poor site selection and improper planning gradually emerge.The issues of project implementation area selection and its programming optimization begin to arouse the attention and thinking of the society.Comprehensive analysis of current mainstream optimization theories shows that traditional models generally has problems of low agreement,poor applicability or insufficient solution accuracy,which is difficult to deal with PPAPs' site selection and planning modeling effectively.Therefore,taking policy guidance as the fulcrum and guided by the questions of"where to implement" and "how to optimize portfolio",this paper manages to propose models of high matching degree and strong adaptability with project inherent characteristics,which aims to help improve the project experience and vitality,and provide reliable intellectual support for investment in project-building.expansion and demolition and reconstruction after the end of the 25-year implementation period.Specific research contents are as follows:(1)Research on policy analysis and investment mechanism based on project characteristics.In view of the lack of policy guidance and unclear investment mechanism,this paper treats project characteristics as the logical starting point to conduct policy combing and investment mechanism analysis.Firstly,based on the orientations and characteristics of stakeholders,including investors,contractors,beneficiaries and the public,this paper sorts out their objectives and demands,which provides supporting materials for subsequent processes;Next.summarize project specific characteristics combined with objectives,laying the foundation for subsequent researches;Then,sort out development trend and timing characteristics of relevant policies,and identify the key policy guidance effect as basic guidelines for the research,so as to improve the policy-matching degree of the proposed optimization models;Finally,combined with policy guidance,this paper analyzes and determines the investment mechanism,ensuring high matching degree of the models.(2)Research on two-factor index system establishment based on policy guidance.In view of problems such as index-extracting difficulty,factor missing,screening bias and insufficient decision-making support caused by traditional processes of index extraction,this paper proposes "policy-risk-profit-feedback" closed-loop based on stakeholders' investment claims instead of extracting factors from macro levels such as economy,technology,society and environment,so that an efficient four-dimensional factor set can be established.The factor set contains policy guidance,risk aversion,income chasing and public feedback.Then,considering that some areas should be directly rejected due to policies and regulations,a two-factor index system including veto and optimal selection indexes is established through index definition,combination and elimination.The above ideas based on targets of stakeholders can provide technical reference for scholars to collect evaluation indicators.(3)Research on integrated site selection approaches under intuitionistic fuzzy environment considering decision-makers' risk preference.In view of problems that traditional fuzzy sets fail to reflect hesitation degree,conventional weighting methods one-sidedly measure index importance and mainstream ranking processes seldom consider risk preference,this paper treats intuitionistic fuzzy numbers as the evaluation tool of qualitative factors based on the trade-offs about evaluation index quantity,fuzzy boundaries and evaluation accuracy requirements.Next,considering matrix consistency and entropy distribution characteristics,an adjusted approach combining the Analytic Hierarchy Process and the Entropy is adopted,so that the weight determination process can not only reflect the fuzziness and hesitation,but also make ba lance between subjective importance and decision contribution of indexes.Then,the TODIM ranking framework is extended by combining intuitionistic fuzzy operation logic and its distance measurement,making results fully reflect the risk aversion psychology of the decision maker and improve the method practicality.(4)Research on the portfolio optimization model and algorithm considering poverty alleviation effect and policy constraints.In view of problems that traditional portfolio models do not fit well and optimization results are not good,this paper analyzes investment objectives and demands at the strategic,project and resource levels,summarizes the specific portfolio characteristics,and forms an "objective-constraint" optimization model under the effects of project goals,policy guidance,regulations and grid connection requirements.For the objectives,considering that the projects have double tasks of power generation and poverty alleviation,this paper uses the number of poor households assisted to represent the poverty alleviation effect,so that the lowest cost and the best poverty alleviation effect are treated as two optimization objectives;For model constraints,with the consideration of the requirements of relevant policies,grid construction and resource consumption,installation capacity is used as the constraint;For solving algorithms,based on the population fitness distribution,and adaptive adjustment of individual reproductive probability,optimization algorithm is improved with non-dominated sorting,crowding degree calculation,elite strategy and adaptive genetic operator.which can effectively deal with problems of premature convergence,poor solution and probability solidification and improve stability of the solution set.The improved algorithm can enrich the theoretical system of intelligent algorithm.(5)Research on planning scheme selection model and solving algorithm based on fairness and efficiency theory.In view of the problem that the traditional processes only consider the efficiency measurement results and does not deal with the solution deviation of small sample data,this paper summarizes the specific representations of fairness and efficiency factors based on the dual perspectives of the project life cycle and the stakeholders.Firstly,fairness demands are turned into calculable indexes,which subsequently serves for the sample preliminary screening process by benchmarking project and clustering algorithm.In this way,the alternatives who perform poorly in the fairness aspect can be identified and eliminated,which greatly fits the basic concept of government-investing projects in maintaining social fairness.Then,efficiency factors are divided into input and output variables so that the Data Envelopment Analysis algorithm can measure the efficiency.Taking the possible estimation bias caused by small samples into consideration,the bootstrapping method based on resampling is introduced to expand the sample and correct the efficiency value,which can ensure the accuracy of efficiency measurement.According to the corrected efficiency value,the optimal ranking is obtained.The aforementioned ideas of model building can be extended to other government-investing projects in scheme selection or efficiency analysis,which can improve the fit between the model and the project,and the improved data analysis algorithm can also enrich the theoretical system of efficiency measurement. |
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